| 書(shū)目名稱(chēng) | Causation in Population Health Informatics and Data Science | | 編輯 | Olaf Dammann,Benjamin Smart | | 視頻video | http://file.papertrans.cn/223/222640/222640.mp4 | | 概述 | Reviews intersections between epidemiology, public health, computation, informatics, and science philosophy.Suggests a new theory for the integration of epidemiology, public health, computation, infor | | 圖書(shū)封面 |  | | 描述 | .Marketing text: This book covers the overlap between informatics, computer science, philosophy of causation, and causal inference in epidemiology and population health research. Key concepts covered include how data are generated and interpreted, and how and why concepts in health informatics and the philosophy of science should be integrated in a systems-thinking approach. Furthermore, a formal epistemology for the health sciences and public health is suggested.. .Causation in Population Health Informatics and Data Science?.provides a detailed guide of the latest thinking on causal inference in population health informatics. It is therefore a critical resource for all informaticians and epidemiologists interested in the potential benefits of utilising a systems-based approach to causal inference in health informatics.. | | 出版日期 | Book 2019 | | 關(guān)鍵詞 | Causation; Epidemiology; Informatics; Illness; Philosophy; causal inference | | 版次 | 1 | | doi | https://doi.org/10.1007/978-3-319-96307-5 | | isbn_softcover | 978-3-030-07174-5 | | isbn_ebook | 978-3-319-96307-5 | | copyright | Springer Nature Switzerland AG 2019 |
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